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Background, aim, and scope Facing the threat of oil depletion and climate change, a shift from fossil resources to renewables is ongoing to secure long-term low carbon energy supplies. In view of the carbon dioxide reduction targets agreed upon in the Kyoto protocol, bioethanol has become an attractive option for one energy application, as transport fuel. Many studies on the LCA of fuel ethanol have been conducted, and the results vary to a large extent. In most of these studies, only one type of allocation is applied. However, the effect of allocation on outcomes is of crucial importance to LCA as a decision supporting tool. This is only addressed in a few studies to a limited extent. Moreover, most of the studies mainly focus on fossil energy use and GHG emissions. In this paper, a case study is presented wherein a more complete set of impact categories is used. Land use has been left out of account as only hectare data would be given which is obviously dominated by agriculture. Moreover, different allocation methods are applied to assess the sensitivity of the outcomes for allocation choices. Materials and methods This study focuses on the comparison of LCA results from the application of different allocation methods by presenting an LCA of gasoline and ethanol as fuels and with two types of blends of gasoline with ethanol, all used in a midsize car. As a main second-generation application growing fast in the USA, corn stover-based ethanol is chosen as a case study. The life cycles of the fuels include gasoline production, corn and stover agriculture, cellulosic ethanol production, blending ethanol with gasoline to produce E10 (10% of ethanol) and E85 (85% of ethanol), and finally the use of gasoline, E10, E85, and ethanol. In this study, a substantially broader set of eight environmental impacts is covered. Results LCA results appear to be largely dependent on the allocation methods rendered. The level of abiotic depletion and ozone layer depletion decrease when replacing gasoline by ethanol fuels, irrespective of the allocation method applied, while the rest of the impacts except global warming potential are larger. The results show a reduction of global warming potential when mass/energy allocation is applied; in the case of economic allocation, it gives contrary results. In the expanded systems, global warming potential is significantly reduced comparing to the ones from the allocated systems. A contribution analysis shows that car driving, electricity use for cellulase enzyme production, and ethanol conversion contribute largely to global warming potential from the life cycle of ethanol fuels. Discussion The reason why the results of global warming potential show a reverse trend is that the corn/stover allocation ratio shifts from 7.5 to 1.7 when shifting from economic allocation to mass/energy allocation. When mass/energy allocation is applied, both more credits (CO 2 uptake) and more penalties (N 2 O emission) in agriculture are allocated to stover compared to the case of economic allocation. However, more CO 2 is taken up than N 2 O (in CO 2 eq.) emitted. Hence, the smaller the allocation ratio is between corn and stover, the lower the share of the overall global warming emissions being allocated to ethanol will be. In the system expansion approach, global warming potentials are significantly reduced, resulting in the negative values in all cases. This implies that the system expansion results are comparable to one another because they make the same cutoffs but not really to the results related to mass, energy, and economic value-based allocated systems. Conclusions The choice of the allocation methods is essential for the outcomes, especially for global warming potential in this case. The application of economic allocation leads to increased GWP when replacing gasoline by ethanol fuels, while reduction of GWP is achieved when mass/energy allocation is used as well as in the system where biogenic CO 2 is excluded. Ethanol fuels are better options than gasoline when abiotic depletion and ozone layer depletion are concerned. In terms of other environmental impacts, gasoline is a better option, mainly due to the emissions of nutrients and toxic substances connected with agriculture. A clear shift of problems can be detected: saving fossil fuels at the expense of emissions related to agriculture, with GHG benefits depending on allocation choices. The overall evaluation of these fuel options, therefore, depends very much on the importance attached to each impact category. Recommendations and perspectives This study focuses only on corn stover-based ethanol as one case. Further studies may include other types of cellulosic feedstocks (i.e., switchgrass or wood), which require less intensive agricultural practice and may lead to better environmental performance of fuel ethanol. Furthermore, this study shows that widely used but different allocation methods determine outcomes of LCA studies on biofuels. This is an unacceptable situation from a societal point of view and a challenge from a scientific point of view. The results from applying just one allocation method are not sufficient for decision making. Comparison of different allocation methods is certainly of crucial importance. A broader approach beyond LCA for the analysis of biorefinery systems with regard to energy conservation, environmental impact, and cost–benefit will provide general indications on the sustainability of bio-based productions.

Purpose The purpose of this paper is to supply an open method for weighting different environmental impacts, open to basically different evaluation approaches and open to easy revisions. From the partial, diverse and conflicting weighing methods available, a most consistent and flexible meta-method is constructed, allowing for a transparent discussion on weighting. Methods The methods incorporated are as general as possible, each single one being as pure as possible. We surveyed encompassing operational methods for evaluation, applicable in LCA and in larger systems like countries. They differ in terms of modelling, as to midpoint or as to endpoint; as to evaluation set-up, in terms of collective preferences or individual preferences; and as to being either revealed or stated. The first is midpoint modelling with collectively stated preferences, with operational weighting schemes from Dutch and US government applications. Second is the LCA-type endpoint approach using individual stated preferences, with public examples from Japan and the Netherlands. The third is the integrated modelling approach by economists. Results All methods are internally inconsistent, as in terms of treatment of place and time, and they are incomplete, lacking environmental interventions and effect routes. We repaired only incompleteness, by methods transfer. Finally, we combined the three groups of methods into a meta-weighting method, aligned to the ILCD Handbook requirements for impact assessment. Application to time series data on EU-27 consumption shows how the EU developed in terms of overall environmental decoupling. Conclusions The disparate methods available all can be improved substantially. For now, a user adjustable meta-method is the best option, allowing for public discussion. A flexible regularly updated spreadsheet is supplied with the article.

Goal, Scope and BackgroundIn the recently published (Dutch) Handbook on LCA, economic allocation is advised as baseline method for most allocation situations in a detailed LCA. Although the Handbook on LCA aimed to provide a ‘cookbook’ with operational guidelines for conducting each step of an LCA, this was not completely achieved for the allocation step. The guidelines for allocation largely remained at the level of principles. This restricted elaboration of economic allocation may hamper application in practice. Therefore, this paper elaborates some examples applying economic allocation.MethodTwo concepts are of particular importance when applying economic allocation: functional flow and multi-functional process. The definitions of these concepts are presented and discussed. The basic principle of economic allocation is that having determined the various functional flows of a multi-functional process, all other flows need to be allocated to these functional flows according to their shares in the total proceeds. Proceeds are based on prices and these are not always easy to determine for a process. A summary of possible solutions for different problems when determining prices is given.Results and DiscussionThe examples presented focus on co-production and various recycling situations. All examples are hypothetical in order to avoid discussions on the data. The examples show that the prices of the functional flows determine the allocation results. It is of importance to have correct information on the relative prices of the functional flows at stake, especially whether they are negative or positive. Learning from these examples, we establish a decision tree for economic allocation. The decision tree is meant for identifying and handling multi-functionality situations starting from a defined (product) system. This decision tree is with minor adaptations also applicable to other allocation methods and has a more general value than for the economic allocation method only.Conclusions and perspectiveThe examples have helped us to establish a decision tree for handling the multi-functionality problem by economic allocation. The examples can be broadened to other materials and allocation situations. We would encourage others to provide other examples and experiences as we expect that these will help to further improve and refine the guidelines and decision tree for economic allocation in future.

Intention, Goal, Scope, BackgroundInput-Output Analysis (IOA) has recently been introduced to Life Cycle Assessment (LCA). In applying IOA to LCA studies, however, it is important to note that there are both advantages and disadvantages.ObjectivesThis paper aims to provide a better understanding of the advantages and disadvantages of adopting IOA in LCA, and introduces the methodology and principles of the Missing Inventory Estimation Tool (MIET) as one of the approaches to combine the strengths of process-specific LCA and IOA. Additionairy, we try to identify a number of possible errors in the use of IOA for LCA purposes, due to confusion between industry output and commodity, consumer’s price and producer’s price.MethodMIET utilises the 1996 US input-output table and various environmental statistics. It is based on an explicit distinction between commodity and industry output.Results and DiscussionMIET is a self-contained, publicly available database which can be applied directly in LCA studies to estimate missing processes.ConclusionBy adopting MILT results in existing, process-based, life-cycle inventory (LCI), LCA practitioners can fully utilise the process-specific information while expanding the system boundary.Recommendations and OutlookMIET will be continuously updated to reflect both methodological developments and newly available data sources. For supporting information sec http:// wwwJeidenuniv.nl/cml/ssp/softwarc/miet.

Climate change and the wish to reduce the dependence on oil are the incentives for the development of alternative energy sources. The use of lignocellulosic biomass together with cellulosic processing technology provides opportunities to produce fuel ethanol with less competition with food and nature. Many studies on energy analysis and life cycle assessment of second-generation bioethanol have been conducted. However, due to the different methodology used and different system boundary definition, it is difficult to compare their results. To permit a direct comparison of fuel ethanol from different lignocelluloses in terms of energy use and environmental impact, seven studies conducted in our group were summarized in this paper, where the same technologies were used to convert biomass to ethanol, the same system boundaries were defined, and the same allocation procedures were followed. A complete set of environmental impacts ranging from global warming potential to toxicity aspects is used. The results provide an overview on the energy efficiency and environmental performance of using fuel ethanol derived from different feedstocks in comparison with gasoline.

Purpose While life cycle assessment (LCA) has standardized methods for assessing emission impacts, some comparable methods for the accounting or impact assessment of resource use exist, but are not as mature or standardized. This study contributes to the existing research by offering a comprehensive comparison of the similarities and differences of different resource indicators, in particular those based on thermodynamics, and testing them in a case study on titania (titanium dioxide pigment) produced in Panzhihua city, southwest China. Materials and methods The system boundary for resource indicators is defined using a thermodynamic hierarchy at four levels, and the case data for titania also follow that hierarchy. Seven resource indicators are applied. Four are thermodynamics-based—cumulative energy demand (CED), solar energy demand (SED), cumulative exergy demand (CExD), and cumulative exergy extraction from the natural environment (CEENE)—and three have different backgrounds: abiotic resource depletion potential, environmental priority strategies, and eco-indicator 99. Inventory data for the foreground system has been collected through on-site interviews and visits. Background inventory data are from the database ecoinvent v2.2. Characterizations factors are based on the CML-IA database covering all major methods. Computations are with the CMLCA software. Results and discussion The scores of resource indicators of the chloride route for titania system are lower than that of the sulfate route by 10–35 %, except in terms of SED. Within the four thermodynamic indicators for resources, CED, CExD, and CEENE have similar scores, while their scores are five orders of magnitude lower than the SED score. Atmospheric resources do not contribute to the SED or CEEND score. Land resources account for a negligible percentage to the SED score and a small percentage to the CEENE score. Non-renewable resources have a dominant contribution to all seven resource indicators. The global production of titania would account for 0.12 and 0.14 % of the total anthropogenic non-renewable resource demand in terms of energy and exergy, respectively. Conclusions First, we demonstrate the feasibility of thermodynamic resource indicators. We recommend CEENE as the most appropriate one within the four thermodynamic resource indicators for accounting and characterizing resource use. Regarding the case study on the titania produced in China, all the resource indicators except SED show that the sulfate route demands more resource use than the chloride route.

Background, aim, and scope Management of the medical waste produced in hospitals or health care facilities has raised concerns relating to public health, occupational safety, and the environment. Life cycle assessment (LCA) is a decision-supporting tool in waste management practice; but relatively little research has been done on the evaluation of medical waste treatment from a life cycle perspective. Our study compares the environmental performances of two dominant technologies, hazardous waste incineration (HWI) as a type of incineration technology and steam autoclave sterilization with sanitary landfill (AL) as a type of non-incineration technology, for specific medical waste of average composition. The results of this study could support the medical waste hierarchy. Materials and methods This study implemented the ISO 14040 standard. Data on steam autoclave sterilization were obtained from an on-site operations report, while inventory models were used for HWI, sanitary landfill, and residues landfill. Background data were from the ecoinvent database. The comparative LCA was carried out for five alternatives: HWI with energy recovery efficiencies of 0%, 15%, and 30% and AL with energy recovery efficiencies of 0% and 10%. Results The assumptions on the time frame for landfill markedly affect the impact category scores; however, the orders of preference for both time frames are almost the same. HWI with 30% energy recovery efficiency has the lowest environmental impacts for all impact categories, except freshwater ecotoxicity. Incineration and sanitary landfill processes dominate global warming, freshwater aquatic ecotoxicity, and eutrophication of incineration and non-incineration alternatives, respectively. Dioxin emissions contribute about 10% to human toxicity in HWI without energy recovery alternatives, and a perturbation analysis yielded identical results. As regards eutrophication, non-incineration treatments have an approximately sevenfold higher impact than incineration treatments. Discussion The differences between short-term and long-term time frame assumptions mainly are decided by heavy metals dissolved in the future leachate. The high heat value of medical waste due to high contents of biomass, plastic, and rubber materials and a lower content of ash, results in a preference for incineration treatments. The large eutrophication difference between incineration and non-incineration treatments is caused by different N element transformations. Dioxin emission from HWI is not the most relevant to human toxicity; however, large uncertainties could exist. Conclusions From a life cycle perspective, the conventional waste hierarchy, implying incineration with energy recovery is better than landfill, also applies to the case of medical waste. The sanitary landfill process is the key issue in non-incineration treatments, and HWI and the subsequent residues landfill processes are key issues in incineration treatments. Recommendations and perspectives Integrating the medical waste hierarchy and constructing a medical waste framework require broader technologies to be investigated further, based on a life cycle approach.

Reducing demand by increasing end-use energy efficiency on the demand side of energy systems may also have advantages in reducing fossil dependency and greenhouse gas (GHG) emissions on the supply side. This paper addresses interactions between energy supply- and demand-side policies, by estimating the impact of measures addressing end-use energy efficiency and small-scale renewables uses in terms of (1) avoided large-scale electricity generation capacity, (2) final energy consumption, (3) share of renewables in final energy and (4) reduction of GHG emissions. The Portuguese energy system is used as a case study. The TIMES_PT bottom-up model was used to generate four scenarios covering the period up to 2020, corresponding to different levels of efficiency of equipment in buildings, transport and industry. In the current policy scenario, the deployment of end-use equipment follows the 2000–2005 trends and the National Energy Efficiency Action Plan targets. In the efficient scenarios, all types of equipment can be replaced by more efficient ones. Results show that aggressive demand-side options for the industry and buildings sector and the small-scale use of renewables can remove the need for the increase in large-scale renewable electricity capacity by 4.7 GW currently discussed by policy makers. Although these measures reduce total final energy by only 0–2 %, this represents reductions of 11–14 % in the commercial sector, with savings in total energy system costs of approximately 3,000 million euros 2000 —roughly equivalent to 2 % of the 2010 Portuguese GDP. The cost-effectiveness of policy measures should guide choices between supply shifts and demand reduction. Such balanced policy development can lead to substantial cost reductions in climate and energy policy.

Linoleum floor coverings are composed of linseed oil, vegetable oils, wood flour, and limestone, compressed on a jute foundation. An environmental life cycle assessment (LCA) for linoleum aimed to evaluated the environmental performance of this product and identify areas for improvement. The unit was 2000 square meters of linoleum suitable for office use, with a life of 20 years. A contribution analysis identified the main contributing processes. Sensitivity analysis highlighted the strong influences of pigments and the type of maintenance during product use. Data gaps were identified for capital goods and unknown chemicals.